Agricultural Research For Development Research Articles

Despite decades of investment in agricultural research and rice development, the Philippines continues to face stagnation in domestic rice production. This persistent trend, occurring despite a sizable arable land base and large rural workforce, has contributed to the country’s growing reliance on rice imports to meet national food needs. In response, the government has implemented a tariff-based import system designed to fund domestic productivity improvements. While previous studies have explored the technical and environmental constraints affecting rice production, such as irrigation shortfalls, land degradation, and climate variability, few have examined recent national trends using regionally disaggregated data alongside qualitative insights. This study fills that gap by analysing official production statistics from 2013 to 2023 across all regions of the Philippines, complemented by contextual data from farming communities and policy reviews. The results reveal that widespread stagnation is primarily driven by limits to both land expansion and yield growth. However, a handful of regions have significantly increased output in recent years, largely due to targeted public investment in irrigation, improved seed technologies, and institutional support. These cases offer important lessons for policy, while also underscoring the risks posed by climate shocks and competing land uses. By identifying both barriers and enablers of rice sector performance, this research contributes to more regionally responsive and inclusive policy strategies aimed at strengthening food security, rural livelihoods, and agricultural resilience in the face of evolving development challenges.

Agency and behavior change in agricultural research for development: New directions for guiding agri-food system transformations

Image dataset of Taro Leaf Blight disease collected from the West African Sub-Region.

BDHerbalPlants: augmented and curated herbal plants image dataset for classification

Insights and future directions: Applying the One Health approach in international agricultural research for development to address food systems challenges.

Agricultural research for development (AR4D) often relies upon a centralized and mechanistic model of social science research. This is a model in which supposedly unskilled field officers (FOs) are recruited to implement household surveys that have been designed by faraway scientists. We argue that such research practices not only impede data quality and analysis but also devalue the work of FOs. We describe this phenomenon as a process of deskilling: One in which research protocols seek to limit the need for FOs to be skilled and also actively obscure the skilled work that FOs nevertheless do in the field. We link this process to a pervasive conception of “scientific rigor” that is grounded in an ideology of science as impersonal, disembodied, and mechanical. Drawing on feminist science and technology studies (STS), we highlight how the ideology and practice of deskilled research perpetuate colonial hierarchies of knowledge. We outline possibilities for and barriers to achieving more equitable and more generative relationships between scientists and FOs in AR4D.

Abstract Agricultural production statistics underpin diverse research efforts and development activities. Yet despite their critical importance, efforts to collate, update, and harmonize detailed sub-national agricultural production statistics are frequently redundant and incomplete due to the substantial time, effort, and resources required. The persisting lack of coordination and standards in the food systems data community wastes valuable resources and hinders advances in action-oriented food systems knowledge. Here we introduce the HarvestStat sub-national data consortium as an open-source, collaborative, and transparent model to overcome these challenges. HarvestStat is collaboratively producing publicly available databases and datasets for the food systems community and the broader environmental and sustainability sciences by moving beyond closed and disjointed data-gathering efforts. We are guided by core principles of complete data openness—prioritizing high standards of quality assurance; active inclusion—emphasizing involvement from local experts; and collaboration—fostering engagement across communities of data producers and users. We extend an open global call to action, inviting organizations and individuals to engage in advancing this critical agenda.

This article explores a fifteen-year collaborative process of studying women’s empowerment in agricultural research for development using both quantitative and qualitative methods. The article discusses how this deep collaboration has provided new insights into women’s empowerment. These collaborations were based on feminist principles related to both the processes and the content of the work. Mixed methods were used within single projects, across sub-projects in different contexts, and across projects over time. By using qualitative and quantitative methods together, new insights are generated about how joint asset ownership and decision making may or may not be empowering and the importance of agency over time, not just workload, as an indicator of empowerment. In addition, the article discusses what has been learned about the processes of collaboration with partners across disciplines and methodologies, geographies, and time and its value in knowledge formation. HIGHLIGHTS Using mixed methods, global and interdisciplinary research collaborations offer new insights into women’s empowerment. Empowerment emerges as a multifaceted concept both within and across locations. Examples on asset ownership, decision making, and time use illuminate this approach. Success in collaborative research requires long-term funding and strong leadership.

ABSTRACTThis paper contributes a new paradigm for international agricultural development research. It uses machine learning techniques to aid expert diagnosis of development problems in conjunction with New Structural Economics (NSE) to analyse and design policies to enable effective rural transformation. It conducts a multi‐country, multi‐regional, multi‐level and multi‐dimensional analysis in Bangladesh, China, Indonesia, and Pakistan to identify stage segmentations of rural transformation and examine stagewise associate policies and applicable learnings across each dimension. By presenting structured stages of rural transformation, we provide guidance on designing dynamic comparative‐advantage‐adapting policies that are able to adapt at each stage. This analytical procedure can serve other relevant agricultural development studies.

Abstract Water footprint (WF) assessment has emerged as a vital tool for understanding and managing agricultural water consumption amid increasing water scarcity. This review synthesizes current knowledge and methodological developments in agricultural WF research, examining both volumetric and Life Cycle Assessment approaches. We analyze key methodological challenges, including water component differentiation, effective precipitation estimation, and calculation standardization across spatial scales. Recent trends show a shift from global assessments toward regional analyses, enabling precise water management strategies. The review evaluates WF reduction methods, demonstrating that optimized crop patterns and improved agricultural practices can significantly reduce water consumption. Integration of hydrological models with WF assessments shows promise for improving accuracy. Climate change, with varying regional impacts, emerges as a critical factor influencing future WF calculations. While WF methodology offers valuable insights for sustainable water management, its practical application requires careful consideration of regional contexts and limitations.

A comprehensive image dataset for the identification of lemon leaf diseases and computer vision applications.

Wheat is one of the most important cultivated plants of major importance in the food industry. Bread is obtained from its grains, which is a staple food for the world's population, as it provides many nutrients, being a rich source of carbohydrates, proteins and vitamins. The aim of this work was to compare the wheat line A4-10, obtained at the Agricultural Research Development Station Albota with 24 wheat genotypes, which are in the national list of varieties, in the pedoclimatic conditions of the station, in order to obtain a winter wheat variety with superior qualities. Winter wheat, of all cereals, has the longest growing season, covering all seasons, climatic conditions differ from one season to another. That is why the morphological characters of the A4-10 line, obtained in the crop year 2002, were analyzed, compared to the 24 varieties and lines, namely: plant height, length of spikelets, number of spikelets, number of grains in the spikelet, weight and production.

ABSTRACT Smallholder farmers in sub-Saharan Africa (SSA) face increasing challenges from pests and climate change, among other issues. In response to these challenges, international agricultural research for development (R4D) investment is often focused on developing and scaling up techniques and technologies that bolster resilience. However, such approaches are often technocentric and follow linear assumptions of innovation diffusion and adoption, which overlook the complex realities that influence smallholder farmers’ dynamic decisions and engagement with novel techniques. This study used qualitative ethnographic methods to explore the experiences, knowledge construction, motivations, and decision-making of farmers in Western Kenya regarding the extensively researched push-pull technology (PPT). Findings reveal that motives for practicing PPT evolve as farmers respond to emerging realities. Farmers’ practices were motivated by factors such as food culture, resource availability, market demand, social networks, and risk management. Farmers often modify and adapt PPT components rather than simply adopting the practice as taught or shown. Contextual factors such as health, livestock ownership, land tenure, access to information and inputs, cost/benefit trade-offs, and social dynamics interact in complex ways. Ultimately, innovation unfolds as a dynamic process requiring inclusive participation, flexibility for local adaptation, and long-term collaboration with farmers as partners in finding solutions.

This paper aimed to study combinations of some monoecious hemp varieties created at A.R.D.S. Secuieni and evaluate the combined influence of the variety of hemp used, the distance between rows of hemp, and the application of the Secuieni method on seed production. The Secuieni method is a cultivation method for hemp seed that is suitable for mechanical harvesting with grain combined directly from fields. This method consists of reducing the height of plants below 2 m, increasing the field uniformity, increasing seed production (sometimes by over 50%), and reducing the seeding rate from 10–15 kg/ha to 4–5 kg/ha. An experiment was carried out within the Agricultural Research—Development Station Secuieni in an experimental field in the monoecious hemp breeding laboratory. The results obtained during 2019–2023 showed that the influence of the variety led to production increases of 276 Mg·ha−1, which were obtained by the Secuieni Jubileu variety compared to the control variety, Succesiv, which had a yield of 1808 Mg·ha−1. The distance between the rows generated seed yields with values between 1908 Mg·ha−1 and 1967 Mg·ha−1, with statistically insignificant differences. The use of the Secuieni method led to production increases with different degrees of significance compared to the control variant. When analyzing the influence of the interaction between the genotype and the distance between the rows, it was observed that the productions obtained varied between 1767 Mg·ha−1 (Succesiv × 50 cm) and 2121 Mg·ha−1 (Secuieni Jubileu × 70 cm). In the analyzed period, the yields oscillated between 1460 Mg·ha−1 (Zenit × uncut) and 2437 Mg·ha−1 (Secuieni × two cuttings). In the case of the interaction between the distances used and the cuttings applied, the obtained production values varied between 1458 Mg·ha−1 (50 cm × UC) and 2402 Mg·ha−1 (70 cm × c2). At the same time, in the case of the combined influence of the three experimental factors, the application of two cuttings, regardless of the variety and distance used, led to statistically assured production increases compared to the control variant (Succesiv × 50 CM × UC).

The primary objective of this research was to determine the most suitable herbicides, the most effective doses, and the optimal timing for the control of ragweed in sunflower crops. In 2024, an experiment was conducted at the Livada Agricultural Development Research Station, using the randomized block method with 10 variants in 3 repetitions, on an albic Luvisol soil with a pH of 5.1, a clay content of 20.9%, and a humus content of 1.8%.

The importance for multi-dimensional priority-setting of agricultural innovations is growing, given that agricultural technologies usually play multiple roles for smallholder farmers. This study assesses agricultural technologies based on their multi-dimensional impacts in the drylands of sub-Saharan Africa and South Asia. The study applies the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to a set of promising agricultural technologies and uses three outcome criteria: the benefit-cost ratio, poverty reduction, and nutrition security. The technologies are related to important cereals and grain legumes grown in these regions: sorghum, pearl millet, and finger millet; groundnut, cowpea, chickpea, lentil, pigeon pea, and soybean. The results show that the top technologies based on individual criteria can differ from the top technologies identified using a combination of criteria. For example, in semi-arid southern Africa, a promising technology which involves integrated pest management for cowpea ranks among the top five technologies which can reduce poverty. However, the analysis involving TOPSIS shows that nutrition security is more important in that region compared to poverty. As such, the top 5 technologies with the highest multi-dimensional impact for semi-arid southern Africa do not involve a cowpea technology; rather, they are all related to pigeon pea, a nutritious grain legume which is currently more consumed in that region compared to cowpea. One limitation of this study is that it did not consider all the roles of agricultural technologies in the drylands of sub-Saharan Africa and South Asia; this should be considered in future studies involving TOPSIS or other MCDM techniques. Nevertheless, the study shows that TOPSIS can successfully be used for multi-dimensional ex-ante impact assessment of agricultural technologies, and thus can support the prioritization of investments targeting agricultural research for development.

<p>Over the past few decades, advancements in agricultural science and technology have driven significant changes in China’s agriculture. This study uses the Wuqiao Experimental Station, established in 1983 in the North China Plain, as a case study to explore the trajectory of regional agricultural research in China over the past 40 years. By analyzing the keywords of all articles produced at this station, the study reveals shifts in research focus, methods, and agricultural practices over time. The analysis shows that the focus of agricultural research has shifted from yield-centered agricultural production and management (APM) to sustainability-oriented agroecology and environment (AE). Additionally, crop research has deepened, evolving from basic crop management to more detailed studies of plant anatomy, physiology, and advanced methods, including high-throughput sequencing and big data analysis. Despite these advances, concerns have emerged regarding the narrowing of research scope to a limited number of crops, primarily wheat and maize, which may reduce agricultural resilience. Furthermore, while research output has increased, a disconnect persists between scientific research and real-world agricultural challenges, such as heat stress and crop quality. This gap underscores the importance of ensuring that agricultural research remains relevant and addresses pressing issues related to food security and environmental sustainability. This study highlights the need to expand crop diversity, integrate sustainable practices, and adopt cutting-edge research methods to ensure the future resilience of China’s agricultural systems. The findings provide valuable insights into trends and future directions in agricultural research in China, emphasizing the importance of a balanced approach to addressing current and future challenges.<strong></strong></p>

The 20th National Congress of the Communist Party of China pointed out that the agricultural modernization plan will be realized in 2035. Through the use of new technologies, new equipment and new platforms, the new quality productivity will enable the innovative allocation of traditional agricultural production factors and the deep transformation and upgrading of industries, change the traditional production and management methods, bring digitalization into agriculture, and drive the development of rural agriculture as an inevitable trend. This project aims to explore the new quality productivity to empower agricultural development and promote the path of agricultural development research. This paper will take some towns in Anhui Province as an example to study the impact of digital new quality productivity on agricultural development in Anhui province, collect data from agricultural departments and related departments, establish a regression model for empirical analysis, and analyze from three aspects: the improvement degree of rural digital economic infrastructure, the proportion of new rural talents and talent support, and the development degree of rural agricultural digital commerce. Combined with the agricultural bureau and related data for empirical analysis. On the basis of adhering to ecological priority and green development, it is expected to provide theoretical support for the comprehensive upgrading of agriculture, the steady growth of rural economy and the all-round development of rural residents, and gather strength for the comprehensive construction of a socialist modern country.

High-resolution cropland mapping in China’s Huang-Huai-Hai Plain: The coupling of machine learning methods and prior information

The use of innovations and information technology approaches in the agricultural sphere of Ukraine under conditions of global influence has been based on the results of multifaceted long-term research. Our goal was to reveal the peculiarities of the formation of Ukrainian natural science knowledge in historical retrospect using problem-chronological and comparative-historical methods. The analysis of the development of agricultural zoning of the territory of Ukraine has been justified by its theoretical and methodological content, which has served as the scientific basis for the organization and formation of agricultural science and research in the first decades of the 20th century. Attention has been focused on the need for an in-depth study of the peculiarities of different territorial parts of the Russian Empire of the country in connection with the problem of geographical division and the growing demands of economic development. The first developments of geographers and soil scientists regarding the division and mapping of the soil cover of Ukraine on maps have been disclosed, among which is the work of V. V. Dokuchaev, as the author of the mapping technique and theoretical justification of the phenomenon of natural zoning. The work of his follower G. I. Tanfilieva became one of the first attempts at a comprehensive characterization of Ukrainian lands, taking into account zonal and provincial differences. The works of P. A. Tutkovskyi, K. G. Vobloh and other scientists, developers of agro-soil, agro-climatic, geobotanical, geomorphological and physical-geographical zoning of the territory of Ukraine. Based on the gathered sources, data regarding the attempt to establish an agricultural experimentation structure during the first quarter of the 20th century in the Forest-Steppe zone of Ukraine, according to the regional principle, are provided. This initiative involved the operation of two regional agricultural research structures in slightly different areas of the Forest-Steppe. In the right-bank part, agricultural experimentation was carried out by the Kyiv Agricultural Research Station with a number of district institutions, while the left-bank part was served by the Kharkiv Agricultural Research Station, district and specialized research institutions. Accumulated in the first decades of the 20th century natural science experience contributed to the development of theoretical and methodological tools for the further development of agricultural science and research in Ukraine.